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Guidelines for Designing AI Technologies to Support Adult Learning
Jennifer Redding, et al., ACM, 2026/07/10

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This is a comprehensive paper offering 19 'guidelines' for instructional AI systems. I think it may be a popular approach because the overall result is that 'AI should not change anything', exemplified by this sentiment that "instructors... frequently highlighted the alignment of AI tools with their personal instructional approach because using AI tools with contrasting approaches can be a challenge." The tools studied were all 'personal tutoring' tools, and though the authors worked in the Community of Inquiry (CoI) framework the outcome is still by-the-book 'personalized' instruction.

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A visual introduction to information theory
Henry Pinkard, Laura Waller, arXiv, 2026/07/10

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I learned this stuff in grad school when I was studying Fred Dretske's Knowlegedge And The Flow Of Information and recognizedIt immediately when I later encountered M.G. Moore's theory of transactional distance. It's the foundation of instructivist learning theories. This 'introduction' goes into a lot of detail, but will reward a careful reading. I didn't think information theory is the foundation of knowledge, but it's still useful to know.

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Game Design + Pedagogy + Leadership = Experiential Leadership
Clark Aldrich, 2026/07/10

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Not a bad post drawing similarities between game design, instruction and leadership, all leading toward a concept Clark Aldrich calls 'experiential leadership' (because everyone knows new leadership theories are where the big money is). The best bit is the chart comparing aspects and timelines of the three; it's worth a critical look.

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Thinking Like a Network 2.0
Curtis Ogden, Network Weaver, 2026/07/10

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I've argued at length over the years in favor of network organization of, well, everything. It's important to understand what this entails. This article offers a good list (quoted): adaptability instead of control; contribution before credentials; giving first, not taking; resilience and redundancy instead of rock stardom; diversity and divergence rather than the usual suspects and forced agreement; intricacy and flow, not bottlenecks and hoarding; self-organization and emergence rather than permission and the pursuit of perfection; shift focus from core to the periphery; from working in isolation to working with others and/or out loud; from “Who’s the Leader?” to “We’re the Leaders!" I know, it's a long list, and your internal sense of value resists mightily giving up power, control and wealth. But ask - who made you value these things? How well are they serving you?

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Before you build AI agents, build your company brain first
Amar Dhaliwal, valueIQ's Newsletter, valueIQ, 2026/07/10

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Almost the only resource LinkedIn is showing me these days (as, I think, it tries to make mobile web browsing useless) is some or another claim that your AI model needs structured data (such as semantic graphs or ontologies) in order to work. This article isn't one of the LinkedIn articles (it's an email subscription) but it carries similar advice. I disagree. Yes, you should provide your AI with a lot of context. But the context doesn't need to be structured like computer code.

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We publish six to eight or so short posts every weekday linking to the best, most interesting and most important pieces of content in the field. Read more about what we cover. We also list papers and articles by Stephen Downes and his presentations from around the world.

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